fix: qc tags and grouping

src/dynamic_foraging_processing/qc/_core/builder.py

@@ -1,16 +1,16 @@
 """Assemble the dynamic foraging ``QualityControl`` object.
 
-Collects a flat list of metrics (behavior + contract QA) into a single
-``QualityControl``, wiring up ``default_grouping`` so the QC portal lays out
-``behavior`` and ``test_suite`` as sibling top-level groups.
+Collects a flat list of metrics (behavior + contract QC) into a single
+``QualityControl``, wiring up ``default_grouping`` so the QC portal groups
+metrics by their ``type`` and ``test_suite`` tags.
 """
 
 import typing as t
 
 from aind_data_schema.core.quality_control import QCMetric, QualityControl
 
 #: Tag keys laid out as siblings at the top level of the QC portal.
-DEFAULT_GROUPING = ["behavior", "test_suite"]
+DEFAULT_GROUPING = [("type", "test_suite")]
 
 
 def build_quality_control(
@@ -26,9 +26,9 @@ def build_quality_control(
     Parameters
     ----------
     metrics : list of QCMetric
-        All metrics (behavior + contract QA).
+        All metrics (behavior + contract QC).
     default_grouping : list of str, optional
-        Tag keys the portal groups by. Defaults to ``["behavior", "test_suite"]``.
+        Tag keys the portal groups by. Defaults to ``[("type", "test_suite")]``.
     allow_tag_failures : list of str, optional
         Tag values whose metric failures should not fail the overall QC.
     key_experimenters : list of str, optional

src/dynamic_foraging_processing/qc/processed/behavior.py

@@ -146,8 +146,8 @@ def side_bias_result(side_bias: np.ndarray, results_folder: t.Optional[str] = No
     -------
     QCResult
         Passes when ``abs(mean_bias) < 0.5``. Fails when the column is empty or
-        all ``nan`` (``mean_bias`` is ``nan``). Tagged ``{"behavior": ...}`` and
-        referencing the side-bias plot.
+        all ``nan`` (``mean_bias`` is ``nan``). Tagged
+        ``{"type": "Average_Side_Bias"}`` and referencing the side-bias plot.
     """
     values = np.asarray(side_bias, dtype=float)
     if values.size == 0 or np.all(np.isnan(values)):
@@ -159,9 +159,9 @@ def side_bias_result(side_bias: np.ndarray, results_folder: t.Optional[str] = No
         name=name,
         value=mean_bias,
         passed=bool(abs(mean_bias) < 0.5),  # nan comparisons are False -> fails
-        description="Average side bias across the session (right is positive).",
+        description="Average side bias should be less than 0.5",
         reference=_plot_reference(SIDE_BIAS_PLOT, results_folder),
-        tags={"behavior": name},
+        tags={"type": "Average_Side_Bias"},
     )
 
 
@@ -203,7 +203,7 @@ def lick_interval_results(
             passed=value < limit,
             description=f"{name} of inter-lick intervals; passes when < {limit}.",
             reference=_plot_reference(LICK_INTERVALS_PLOT, results_folder),
-            tags={"behavior": name},
+            tags={"metric": name, "type": "Lick_Interval"},
         )
         for name, value, limit in specs
     ]

tests/test_qc/test_behavior.py

@@ -49,7 +49,7 @@ def test_side_bias_result_pass_and_fail():
     assert passing.passed is True
     assert passing.value == pytest.approx(0.0)
     assert passing.reference == _behavior.SIDE_BIAS_PLOT
-    assert passing.tags == {"behavior": "average side bias"}
+    assert passing.tags == {"type": "Average_Side_Bias"}
 
     failing = _behavior.side_bias_result(np.array([0.8, 0.9, 1.0]))
     assert failing.passed is False
@@ -75,7 +75,7 @@ def test_lick_interval_results_names_and_count():
         "Artifact Percent (%)",
     ]
     assert all(r.reference == _behavior.LICK_INTERVALS_PLOT for r in results)
-    assert all(r.tags == {"behavior": r.name} for r in results)
+    assert all(r.tags == {"metric": r.name, "type": "Lick_Interval"} for r in results)
 
 
 def test_reference_includes_results_folder_name():